Method Drift›Mixture-of-experts routing
Superseded baseline#243 of 1,370 most-superseded
Vision Transformers
Mixture-of-experts routing
superseded — cited as a baseline and beaten by newer methods
2 papers critique it · 0 beat it on benchmarks
What papers say
Verbatim critique sentences, each from a paper that cites Vision Transformers as a baseline.
“these gains come at the expense of substantial computational overhead (e.g., Restormer demands 367 GFLOPs for 256×256 images), posing a bottleneck for high-resolution image processing”
— M2Restore: Mixture-of-Experts-based Mamba-CNN Fusion Framework for All-in-One Image Restoration“Using ViTs into LLIE pipelines has demonstrated superior performance in challenging environments; however, the high computational cost of ViTs and their tendency to overfit require architectural innovations, such as the use of lightweight modules or task-specific adaptations.”
— ISALux: Illumination and Segmentation Aware Transformer Employing Mixture of Experts for Low Light Image Enhancement
Newer alternatives
Recent methods in the same sub-problem, not yet superseded in the knowledge base.